Implementation of Flooding Free Routing in Smart Grid

Smart Grid is a communication and automatic control capabilities in electric power grid system for improving efficiency, reliability, management, capabilities and security of electric power grid. Routing is important in Smart Grid to send data from one point to another point. Routing in Smart Grid is necessary to search /identify destination point/node for communication and to computer the best available route in the network topology among which the data to be sent during communication. Smart Grid can be a combination of fixed nodes (home appliances, smart meter, control centre, etc.) but the nature of communication between fixed nodes is dynamic due to the switch on/off or the fluctuation in electricity flow. Therefore the fixed nodes can also be disappeared from the network topology in Smart Grid. Existing routing protocols for Smart Grid are based on flooding mechanism. We would like to examine the feasibility of flooding free routing in Smart Grid. Then we will propose a flooding-free routing for Smart.

Revolution of Energy Storage System in Smart Grids

Electrical grid is no longer featured in a conventional way nowadays. Today, the growing of new technologies, primarily the distributed renewable energy sources and electric vehicles, has been integrated with the distribution networks causing several technical issues. As a result, the penetration of the renewable energy sources can be limited by the utility companies. Smart grid has been emerged as one of the solutions to the technical issues, hence allowing the usage of renewable and improving the energy efficiency of the electrical grid. The challenge is to develop an intelligent management system to maintain the balance between the generation and demand. This task can be performed by using energy storage system. As part of the smart grid, the deployment of energy storage system plays a critical role in stabilizing the voltage and frequency of the networks with renewable energy sources and electric vehicles. This book chapter illustrates the revolution and the roles of energy storage for improving the network performance.

Modeling and Operating Strategies of Micro-Grids for Renewable Energy Communities

Electric power is flexible, easily controlled and is used in everyone's daily life. Humans can't use other form of energy except electric power because electric power, is one of the main factor to economic development, improved health care, poverty alleviation, and cleaner environment for a society. According to an estimate people more than 1.5 billion worldwide don't have sufficient access to electric power due to inaccessibility, electrification via traditional centralized form of grid was not a feasible option. This led to phenomenal research interest in microgrid based energy supply. Microgrids are low voltage network's that are designed to generate, transmit and distribute electrical energy. These grids accomplish specific goals such as cost reduction, CO2 emission reduction, reliability and diversification of energy sources. Microgrids are an ideal way to integrate renewable energy resources in the local community and allow consumer participation in an energy enterprise. In this chapter, we present a comprehensive overview of recent advancement in Microgrids.

Efficient Control Strategies to Optimize Electricity Cost and Consumer Satisfaction

Increasing consumer demand of electricity is difficult for the conventional power system network to handle, regarding both cost and infrastructure. Instead of expanding the expensive infrastructure, power engineers are now focusing on improving efficiencies and effectiveness of existing power networks. This chapter specifically focuses on low cost electricity supply, by introducing the novel concept of digital energy management system in hybrid AC/DC micro-grid. It is assumed that grid is partially powered by time varying renewable resources. The concept of minimizing time average electricity cost is introduced by efficient utilization of these renewable resources and by making the load demands more flexible to operate while taking converter losses into account. Real time pricing model is introduced to elaborate the advantage of time-of-use pricing. Control decisions will be achieved by proposing a load scheduling and hybrid switching (LSHS) algorithm. This algorithm will be capable of supplying low cost electricity while serving the load demands under specific delay bounds.

Battery Management Based on Predictive Control and Demand-Side Management

The chapter is intended to introduce the predictive control based energy management strategy for the grid connected renewable systems in order to achieve an effective demand side management strategy. Grid connected Photovoltaic battery system as being popular and extensively used has been discussed in this chapter .Conventionally, battery storage has been used to store surplus energy produced and meet the load demand with this stored energy. However, such systems do not respond to the grid conditions and violate grid constraints of permissible grid voltage and frequency limits. The operation of the battery depends on the forecast of photovoltaic output and the load demand and as such a predictive control based energy management strategy is needed. A simple optimization problem for such scenarios has also been formulated in great detail to provide readers with an idea for solving such problems. The results of simulations are also discussed.

Measuring Cascading Failures in Smart Grid Networks

Smart Grid is the next generation of the electrical power systems that form from interdependent networks. Cascading failures in such interdependent critical infrastructure is very crucial which can cause wide spread disruption. This chapter is intended to evaluate four different topological metrics in which can be best described and approximated the behavior of cascading failures in interdependent networks by employing two interlinks strategies such as random interlinks addition and degree-degree correlation interlinks. The four chosen topological metrics are algebraic connectivity, effective graph resistance, average betweenness centrality, and average distance. Throughout the chapter, analytical study of each metric are discussed and also compared with numerical simulation based on sandpile dynamics load distribution.

Smart Grid and Demand Side Management

Energy becoming more and more crucial and critical in the civilized populations and locates itself as one of the major requirements of living standards. Obtaining the energy from fossil fuels still is one of the common sources of energy production; however, there is a common understanding of increasing the potential use of renewables, carbon capture and storage, energy efficiency and intelligence and smart applications for collecting, distributing and transmission of the energy between the supply and demand locations. Those applications and generating the new policies, roadmaps in order to make an energy revolution and increase the usage of low-carbon energy technologies targeting the decrease of energy related emissions. In this chapter, the authors explains the common issues about smart grid and demand side management and possible use artificial intelligence and metaheuristic algorithms for smart grid and demand side management optimization and scheduling.

Energy Cost Saving Tips in Distributed Power Networks

This chapter studies energy cost saving strategies in power networks. A prosumer is a user that not only consumes electricity, but can also produce and store electricity. Three tips are considered: distributed power network architecture, peak energy shaving with the integration of prosumers' contribution and prosumers market. The proposed distributed power network architecture reduces significantly the transmission costs and can reduce significantly the global energy cost up to 42 percent. Different types of prosumer who use self-charging renewable energy systems, are able to intelligently buy energy from, or sell it, to the power grid. Therein, prosumers interact during the purchase or sale of electric power using a double auction with negotiation mechanism. Using a two-step combined learning and optimization scheme, each prosumer can learn its optimal bidding strategy and forecast its energy production, consumption and storage. Our simulation results show that the integration of prosumers can reduce peak hour costs up to 17 percent and 6 percent for eligible prosumers.

Geographic Information System for the Smart Grid

This chapter presents fundamental concepts and purpose of the Geographic Information System (GIS) to understand, deploy, monitor, and control the Smart Grid (SG). To enable existing power grid for two-way electricity flow, there is a need to consider deployment of a number of advanced technologies. The SG will have a huge number of devices which are capable of information exchange across the whole electricity network. The GIS is a computer based tool which has the ability to display useful information primarily in the form of labeled digital maps. This capability is useful for transformation of conventional electric grid to a SG by finding suitable locations for timely and economically affordable installation of SG components. Although GIS is in use for electric utilities, new research and advancements in enabling technologies have made it more suitable to play a bigger role in the SG.

Dynamic Trust Elective Geo Routing to Secure Smart Grid Communication Networks

Smart Grid is believed to be the next generation of electrical power system. It integrate the existing electrical power infrastructure with Information Communication Technology (ICT) to achieve two way communication and become smart. A high level of network availability is therefore required to guarantee two-way flows of electricity and information among smart electrical units. The wireless mesh network infrastructure can provide redundant routes for the Smart Grid communications so as to ensure the network availability. However, the wireless connection is vulnerable to cyber-attacks. In this paper, we propose a Fuzzy-Based Energy Aware Trusted Geo-Routing (FEATGR), which can decide the optimal end-to-end path between any source and destination by effectively leveraging the energy consumption, location and trust metrics. The extensive simulation studies have confirmed that FEATGR is capable to achieve the stable and secured routing performance so as to guarantee the high level of network availability for wireless Smart Grid communications.